Why are some states doing so poorly on the AHR?
This analysis seeks to explore the relationship between the finance score and the costs associated with transportation construction and maintenance in urban vs rural states
## Rows: 750 Columns: 28## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (14): ., Report Edition, Rural Interstate Poor Condition, Number of Mile...
## dbl (1): Year##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Sum of Spending in All States
| Year | Total_Spending | Admin_Spending | Maint_Spending | Capital_Spending |
|---|---|---|---|---|
| 2005 | $98,905,495.00 | $6,359,601.00 | $15,944,218.00 | $50,309,238.00 |
| 2006 | $99,609,053.00 | $7,015,900.00 | $17,071,805.00 | $54,662,456.00 |
| 2007 | $109,714,183.00 | $7,914,254.00 | $20,004,734.00 | $62,570,465.00 |
| 2008 | $118,364,945.00 | $10,777,381.00 | $18,707,307.00 | $62,906,654.00 |
| 2009 | $117,691,336.00 | $9,247,068.00 | $20,762,054.00 | $65,102,982.00 |
| 2011 | $124,160,011.00 | $8,486,420.00 | $20,446,877.00 | $66,595,966.00 |
| 2012 | $132,078,139.00 | $8,614,245.00 | $21,235,771.00 | $70,152,840.00 |
| 2013 | $131,216,540.00 | $8,191,756.00 | $21,187,578.00 | $68,864,703.00 |
| 2014 | $142,130,109.00 | $8,155,604.00 | $22,519,783.00 | $74,336,715.00 |
| 2015 | $145,013,710.00 | $8,845,187.00 | $22,812,987.00 | $74,895,863.00 |
| 2016 | $139,114,797.00 | $8,805,149.00 | $23,334,525.00 | $71,752,847.00 |
| 2018 | $151,785,475.00 | $9,520,230.00 | $26,554,566.00 | $77,145,873.00 |
| 2019 | $157,763,506.00 | $10,083,635.00 | $27,457,186.00 | $78,869,455.00 |
## Total_increase Admin_increase Maint_increase Capit_increase
## [1,] 59.51% 58.56% 72.21% 56.77%| Year | Mean_Total_Spending | Mean_Admin_Spending | Mean_Maint_Spending | Mean_Capital_Spending |
|---|---|---|---|---|
| 2005 | 96.70780 | 6.296430 | 15.59245 | 44.12532 |
| 2006 | 76.77893 | 5.658905 | 11.29937 | 39.02704 |
| 2007 | 78.61012 | 6.567648 | 13.32362 | 41.83878 |
| 2008 | 82.21688 | 7.914406 | 13.06733 | 42.66494 |
| 2009 | 87.35376 | 7.662852 | 14.46659 | 45.72699 |
| 2011 | 94.40735 | 7.192401 | 14.19572 | 48.72561 |
| 2012 | 103.43915 | 7.456157 | 14.43227 | 51.42967 |
| 2013 | 100.63841 | 7.143515 | 15.21878 | 49.80954 |
| 2014 | 123.40047 | 7.781953 | 18.86065 | 61.22979 |
| 2015 | 105.90247 | 7.250358 | 15.71685 | 52.22496 |
| 2016 | 90.71018 | 6.704275 | 14.46514 | 45.11075 |
| 2018 | 94.86940 | 6.442822 | 15.95184 | 46.80493 |
| 2019 | 118.78649 | 7.330004 | 18.45981 | 54.64471 |
| Year | Total_Variance | Admin_Variance | Maint_Variance | Capit_Variance |
|---|---|---|---|---|
| 2005 | 18218.899 | 52.39913 | 686.95808 | 2054.256 |
| 2006 | 8874.264 | 37.50792 | 79.12639 | 1107.241 |
| 2007 | 5723.053 | 45.74173 | 132.53958 | 1364.343 |
| 2008 | 5920.812 | 76.29864 | 115.79198 | 1313.300 |
| 2009 | 6778.307 | 65.26375 | 200.63166 | 1203.428 |
| 2011 | 11791.261 | 51.55652 | 182.51441 | 2540.036 |
| 2012 | 14101.667 | 60.26171 | 155.74347 | 2462.963 |
| 2013 | 16028.808 | 56.81206 | 233.66495 | 2767.747 |
| 2014 | 32577.252 | 67.37673 | 480.96445 | 5459.697 |
| 2015 | 14760.678 | 55.30855 | 190.07772 | 3073.081 |
| 2016 | 7032.262 | 45.93955 | 136.12711 | 1378.899 |
| 2018 | 9148.768 | 32.97870 | 186.88097 | 1848.760 |
| 2019 | 27817.718 | 35.38823 | 261.20032 | 2738.361 |
## # A tibble: 13 × 5
## Year Total_Variance Admin_Variance Maint_Variance Capit_Variance
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2005 6.30 4.38 9.14 2.74
## 2 2006 3.05 2.60 0.926 1.26
## 3 2007 1.63 2.50 1.13 1.19
## 4 2008 1.45 2.26 1.14 1.14
## 5 2009 1.68 2.62 1.60 0.976
## 6 2011 2.66 2.48 1.52 1.99
## 7 2012 2.81 2.83 1.20 1.74
## 8 2013 3.26 2.96 1.82 2.04
## 9 2014 5.13 3.23 3.02 3.15
## 10 2015 2.47 2.48 1.28 1.92
## 11 2016 1.40 2.28 0.963 1.03
## 12 2018 1.71 1.56 1.14 1.33
## 13 2019 3.97 1.24 1.23 1.56
Greater Variance In Finance Scores than Performance Scores
New Jersey has by far the worst Finance Score, almost double
## Rows: 50 Columns: 43## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): State
## dbl (42): Urbanization, Tax Burden Overall, Property Tax Burden, Income Tax ...##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.## State Finance Score Performance Score
## 30 New Jersey 7.884 1.758
## 32 New York 3.157 1.322
## 21 Massachusetts 2.960 0.971
## 47 Washington 2.924 0.967
## 8 Delaware 2.780 1.060
## 39 Rhode Island 2.718 2.018
## 9 Florida 2.632 0.753
## 5 California 2.422 1.299
## 20 Maryland 2.102 0.876
## 7 Connecticut 2.022 0.632
## 11 Hawaii 1.824 2.230
## 38 Pennsylvania 1.413 1.216
## 28 Nevada 1.409 0.590
## 3 Arizona 1.398 0.879
## 45 Vermont 1.398 0.438
## 13 Illinois 1.391 1.249
## 6 Colorado 1.379 1.158
## 14 Indiana 1.333 0.956
## 37 Oregon 1.305 0.749
## 36 Oklahoma 1.303 1.181
## 2 Alaska 1.254 2.586
## 29 New Hampshire 1.238 0.622
## 35 Ohio 1.220 0.757
## 1 Alabama 1.151 0.869
## 44 Utah 1.138 0.449
## 23 Minnesota 1.103 0.668
## 10 Georgia 1.062 0.630
## 22 Michigan 1.048 1.181
## 49 Wisconsin 1.018 0.898
## 42 Tennessee 0.807 0.643
## 43 Texas 0.799 0.789
## 12 Idaho 0.777 0.644
## 15 Iowa 0.764 0.938
## 31 New Mexico 0.716 1.052
## 19 Maine 0.621 1.323
## 46 Virginia 0.585 0.511
## 16 Kansas 0.555 0.730
## 41 South Dakota 0.554 0.755
## 33 North Carolina 0.517 0.684
## 18 Louisiana 0.516 1.525
## 50 Wyoming 0.489 0.825
## 27 Nebraska 0.447 1.062
## 24 Mississippi 0.434 0.924
## 4 Arkansas 0.392 0.984
## 17 Kentucky 0.392 0.725
## 26 Montana 0.392 0.829
## 25 Missouri 0.368 0.698
## 40 South Carolina 0.346 1.130
## 34 North Dakota 0.297 0.608
## 48 West Virginia 0.263 1.389Finance STDV, Variance
## [1] 1.231537## [1] 1.516683Performance STDV, Variance
## [1] 0.4358104## [1] 0.1899307Tax, Finance, and Performance Ranking Matrix
Shows the correlations between all rankings Notice that Finance Rank correlates with both cost of living and doing business but nothing else. Neither is correlated with performance rank either.
## Rows: 50 Columns: 28## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (28): Tax Overall Rank, Finance Rank, Performance Rank, Overall Rank, Ca...##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Multiple Regression Analysis
Explores statistical relationships between Finance, Performance, and Localized Costs Ranks
Here’s the CNBC Definitions:
Cost of Doing Business: We measure the strength of each state’s business tax climate, as well as tax burdens for various types of businesses and facilities. We also measure wage and utility costs, as well as the cost of office and industrial space. And we consider incentives and tax breaks that states offer to reduce business costs, with special emphasis on incentives targeted toward development in disadvantaged communities.
Education: We consider the number of higher education institutions in each state as well as long-term trends in state support for higher education. We also consider historically Black colleges and universities (HBCUs), which companies are increasingly seeking to partner with. We look at multiple measures of K-12 education including test scores, class size and spending. We also look at life-long learning opportunities in each state.
Workforce: We measure the educational attainment of each state’s working-age population, as well as which states are attracting college-educated workers and which states are losing them. With skilled workers in particular demand, we consider each state’s concentration of science, technology, engineering and math (STEM) workers. We measure worker productivity based on economic output per job. We look at union membership and right to work laws. And we measure the availability of workers, as well as the diversity of each state’s workforce.
Cost of Living: The cost of living helps drive the cost of doing business. From housing to food and energy, wages go further when the cost of living is low. We measure the states based on an index of costs for basic items.
Overall Rank
## Rows: 50 Columns: 43## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): State
## dbl (42): Urbanization, Tax Burden Overall, Property Tax Burden, Income Tax ...##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.##
## Call:
## lm(formula = Overall.Rank ~ EDUCATION + WORKFORCE + Cost.of.Doing.Business +
## Cost.of.Living)
##
## Residuals:
## Min 1Q Median 3Q Max
## -19.299 -9.618 0.431 9.028 19.268
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.80518 7.30313 0.521 0.6049
## EDUCATION 0.30566 0.11994 2.549 0.0143 *
## WORKFORCE -0.09737 0.12634 -0.771 0.4449
## Cost.of.Doing.Business 0.59189 0.22959 2.578 0.0133 *
## Cost.of.Living 0.05580 0.22069 0.253 0.8016
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 11.46 on 45 degrees of freedom
## Multiple R-squared: 0.4325, Adjusted R-squared: 0.3821
## F-statistic: 8.574 on 4 and 45 DF, p-value: 3.124e-05Finance Rank
##
## Call:
## lm(formula = Finance.Rank ~ EDUCATION + WORKFORCE + Cost.of.Doing.Business +
## Cost.of.Living)
##
## Residuals:
## Min 1Q Median 3Q Max
## -25.8019 -4.9936 -0.5732 8.1290 21.9406
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 18.325130 6.676857 2.745 0.00867 **
## EDUCATION 0.007867 0.109650 0.072 0.94312
## WORKFORCE -0.302485 0.115503 -2.619 0.01198 *
## Cost.of.Doing.Business 0.270176 0.209906 1.287 0.20463
## Cost.of.Living 0.302632 0.201768 1.500 0.14062
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10.48 on 45 degrees of freedom
## Multiple R-squared: 0.53, Adjusted R-squared: 0.4882
## F-statistic: 12.69 on 4 and 45 DF, p-value: 5.418e-07RPP + Overall Score
##
## Call:
## lm(formula = Overall.Score ~ RPP)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.75755 -0.26877 -0.04288 0.16320 1.74333
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.899159 0.645515 -4.491 4.45e-05 ***
## RPP 0.041369 0.006647 6.223 1.14e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4206 on 48 degrees of freedom
## Multiple R-squared: 0.4466, Adjusted R-squared: 0.435
## F-statistic: 38.73 on 1 and 48 DF, p-value: 1.142e-07
******* Finance Score + RPP ************
##
## Call:
## lm(formula = Finance.Score ~ RPP)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.6549 -0.4306 -0.0728 0.1464 4.7173
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.80692 1.37410 -5.681 7.66e-07 ***
## RPP 0.09460 0.01415 6.685 2.23e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8954 on 48 degrees of freedom
## Multiple R-squared: 0.4822, Adjusted R-squared: 0.4714
## F-statistic: 44.69 on 1 and 48 DF, p-value: 2.234e-08
Finance Score + Performance + RPP
##
## Call:
## lm(formula = Finance.Score ~ Performance.Score + RPP)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.8950 -0.3498 -0.0387 0.1381 4.5961
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.60083 1.39511 -5.448 1.82e-06 ***
## Performance.Score 0.28747 0.31612 0.909 0.368
## RPP 0.08951 0.01524 5.873 4.18e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.897 on 47 degrees of freedom
## Multiple R-squared: 0.4911, Adjusted R-squared: 0.4695
## F-statistic: 22.68 on 2 and 47 DF, p-value: 1.275e-07Cost of Living vs Tax Burden
## New names:
## * `` -> ...3## Rows: 510 Columns: 4## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): City, State
## dbl (1): Cost of Living Index
## lgl (1): ...3##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## No trace type specified:
## Based on info supplied, a 'scatter' trace seems appropriate.
## Read more about this trace type -> https://plotly.com/r/reference/#scatter## No trace type specified:
## Based on info supplied, a 'scatter' trace seems appropriate.
## Read more about this trace type -> https://plotly.com/r/reference/#scatterResults
The above results show that when controlling for differences in Workforce and Education, the cost of doing business has a significant impact on the Overall Score, which is the best indicator